Monitoring and management for energy storage devices

ABSTRACT

A monitoring and management system (MMS) includes one or more fiber optic cables arranged within or on portions of an energy storage device. Each fiber optic cable includes multiple optical sensors. At least one of the optical sensors is configured to sense a parameter of the energy storage device that is different from a parameter of the energy storage device sensed by at least another optical sensor of the multiple optical sensors. The MMS includes a light source configured to provide light to the one or more fiber optic cables and a detector configured to detect light reflected by the optical sensors. The detector generates an electrical signal based on the reflected light. A processor is coupled to receive the electrical signal, to analyze the electrical signal, and to determine state of the energy storage device based on analysis of the electrical signal.

TECHNICAL FIELD

This application relates generally to techniques for monitoring and/ormanaging energy storage and/or power systems. The application alsorelates to components, devices, systems, and methods pertaining to suchtechniques.

SUMMARY

Various embodiments described herein involve systems and methods formonitoring and/or managing energy storage devices, power systems andother such devices. In some embodiments, a monitoring and managementsystem (MMS) includes one or more fiber optic cables arranged within oron portions of an energy storage device. Each fiber optic cable includesmultiple optical sensors. At least one of the optical sensors isconfigured to sense a parameter of the energy storage device that isdifferent from a parameter of the energy storage device sensed by atleast another optical sensor of the multiple optical sensors. The MMSincludes a light source configured to provide light to the one or morefiber optic cables and a detector configured to detect light reflectedby the optical sensors. The detector generates an electrical signalbased on the reflected light. A processor is coupled to receive theelectrical signal, to analyze the electrical signal, and to determinestate of the energy storage device based on analysis of the electricalsignal. In some implementations, the multiple fiber optic cablescomprise multi-mode fiber optic cables.

Some embodiments involve a method for monitoring and/or managing anenergy storage device or power system. Light is transmitted into one ormore fiber optic cables, the fiber optic cables arranged within or oncomponents of the energy storage device. Each fiber optic cable includesmultiple optical sensors, at least one of the optical sensors configuredto sense an internal parameter of the energy storage device that isdifferent from a parameter sensed by at least one other optical sensorof the multiple optical sensors. Light reflected by one or more of themultiple optical sensors is detected by a detector that generates anelectrical signal in response to detecting the reflected light. Theelectrical signal is analyzed and to determine the state of the energystorage device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a general block diagram of a monitoring and managementsystem according to embodiments described herein;

FIG. 2 shows a block diagram of a monitoring and management system for abattery;

FIG. 3 illustrates reflected spectra for fiber Bragg grating (FBG)sensors used in a power supply sensing and management system;

FIG. 4 shows an idealized shift in the wavelength spectrum for a FBGsensor deployed on a single mode fiber cable;

FIG. 5 shows the shift in the wavelength spectrum for a FBG sensordeployed on a multi-mode fiber optic cable;

FIG. 6 shows the shift in the wavelength spectrum modulated envelope ofthe FBG sensor of FIG. 5;

FIG. 7 shows a battery with multiple types of sensors arranged within abattery configured to sense multiple battery parameters;

FIG. 8 is a detailed view of the battery of FIG. 7 that shows deploymentof a sensor within an electrode of the battery;

FIG. 9 is a block diagram showing portions of an analyzer used to detectchanges in sensed parameters for power supply monitoring;

FIG. 10 is a block diagram showing portions of an analyzer that uses anon-pixelated photosensitive detector;

FIG. 11 is a photograph of a packaged analyzer; and

FIG. 12 is a flow diagram that illustrates a management process that canbe used for an energy storage device.

Like reference numbers refer to like components; and

Drawings are not necessarily to scale unless otherwise indicated.

DESCRIPTION

Battery management systems that rely on external cell performanceparameters to determine state-of-charge (SOC) and/or state-of-health(SOH) result in conservative overdesign to manage the uncertainty inbattery state-of-charge and battery degradation with aging. Thisreliance on conservative overdesign of batteries has affected thewidespread adoption of clean technologies such as electric vehicles andpower grid storage. Conservative overdesign of batteries arises in partbecause the battery state cannot be fully understood from externalparameters alone. This situation also applies to other types of energystorage devices and/or power generation systems where it is difficult tomeasure internal parameters.

Embodiments described in this disclosure involve optically-based smartmonitoring and management systems which can be used for power generationsystems and/or energy storage devices. The monitoring and managementsystems disclosed herein enable comprehensive real-time performancemanagement and reduce overdesign of power and/or energy systems. Themonitoring and management systems disclosed herein combine embeddedfiber optic sensors to detect internal energy storage/power systemparameters and may also include external sensors to detect externalenergy storage/power system parameters. The outputs from the internaland/or external sensors are used by smart algorithms to infer energystorage/power system state information, and to make predictions such asstate-of-health and remaining useable energy of the energy storagesystem. The approaches disclosed herein are applicable to batteries andbattery packs, fuel cell stacks, turbine-based power systems, and othertypes of energy storage and power generation devices and systems.

FIG. 1 is a block diagram of a monitoring and management system (MMS)100 that can be used for energy storage devices and/or power generationsystems. Multiple internal optical sensors 111-114 are arranged withinthe interior of an energy storage/power system 101 and can be configuredto sense multiple internal properties of the energy storage/power system101. For example, the internal optical sensors 111-114 may measure oneor more parameters such as internal temperature, stress, strain,acceleration, ion concentration, chemistry, and/or other internalparameters of the energy storage/power system 101. The internal opticalsensors 111-114 shown in FIG. 1 sense first, second, and thirdparameters. The first, second and third parameters are different typesof parameters such as temperature, strain, and/or chemistry. In theillustrated example, sensor 111 is a first sensor sensing a firstparameter and sensor 114 is a second sensor also sensing the firstparameter. Sensor 111 and sensor 114 may be located at differentlocations within the energy storage/power system 101 and/or the outputsof sensor 111 and sensor 114 may be combined to yield an average orcomposite value for the first sensed parameter. Alternatively, multiplesensors of the same type can be used to develop a map of the spatialdistribution of one or more parameters at the interior and/or exteriorof the energy storage device or power generation system. Note thatalthough terms first, second, and third are used in this example, theseterms are not intended to imply any hierarchy or priority and are onlyused to distinguish between different sensors and/or parameters.

The internal optical sensors 111-114 are coupled through one or morefiber optic (FO) cables 110 to a light source 120 and internal parameteranalyzer 130. In some cases, the optical sensors 111-114 are disposed ona single FO cable and the optical signals from the sensors aremultiplexed using techniques such as optical time division multiplexing(TDM) and/or optical wavelength division multiplexing (WDM) and/or othervarieties of optical signal multiplexing. The sensors disposed on the FOmay comprise any type (or multiple types) of optical sensor, includingfiber Bragg grating (FBG) sensors and/or etalon or Fabry-Perot (FP)sensors. Both the FBG, etalon, and FP sensors are collectively referredto herein as FO sensors. Although some examples are provided below arebased on FBG sensors, it will be understood that other types of opticalsensors could alternatively or additionally be used in these and otherexamples.

Light source 120 provides light through fiber optic cable 110 to theinternal optical sensors 111-114 where the transmitted light interactswith each sensor 111-114. Each sensor transmits certain wavelengths oflight and reflects certain wavelengths of light. In some cases, somesensors interact differently with the light than other sensors. Forexample, the wavelengths reflected by some sensors may be different fromthe wavelengths reflected by other sensors. Light reflected by thesensors 111-114 is detected by analyzer 130. As described in more detailbelow, analyzer 130 is capable of detecting shifts in the wavelengths oflight reflected from the sensors 111-114, where the wavelength shifts inthe reflected light are indicative of the sensed internal parameters.

The MMS 100 may optionally include an external parameter analyzer 140arranged externally to the energy storage/power system 101 configured tomeasure one or more external parameters, such as current, voltage,and/or power output of the energy storage/power system 101. In someimplementations, the internal parameter analyzer 130 and/or the externalparameter analyzer 140 can be electrically coupled to a managementsystem 150 through output lines 131 and 141, respectively. The internalparameter analyzer 130 provides information about the internalparameters on output line 131 and the external parameter analyzerprovides information about the external parameters on output line 141.The management system 150 typically includes a processor and/or otherelectrical circuitry configured implement various processes that assessenergy storage/power system status based on the information provided bythe internal parameter analyzer 130 and/or the external parameteranalyzer 140. According to various implementations, some aspects of theenergy storage/power system 101, e.g., charge rate and/or charge cyclesin the case of a battery, may be automatically controlled through afeedback output 151 from the management system 150. The managementsystem may use information from the internal parameter analyzer and/orthe external parameter analyzer to make predictions and/or estimationsregarding the state of the energy storage/power system. Thesepredictions and estimations may be developed using theoretical and/orempirical data and may be adaptable based on operational conditions ofthe energy storage/power system, measures of internal and/or externalparameters and/or correlations between the operational conditions andmeasured parameters. Some implementations may provide energystorage/power system monitoring and thus may not include the managementsystem, and/or in some implementations the management system may notprovide feedback to the energy storage/power system.

In some cases, information based on the internal and/or externalparameter analyzers can be developed by the management system 150 andprovided to an operator via an electronic or printed report. Forexample, the management system 150 may compile, analyze, trend, and/orsummarize the internal and/or external parameters, and/or may performother processes based on the internal and/or external parameters, suchas predicting and/or estimating the state of the energy storage/powersystem. The results of these processes and/or other information derivedfrom monitoring the energy storage/power system may be provided in areport that can be displayed graphically or textually or in anyconvenient form to an energy storage/power system operator and/or may beprovided to another computer system for storage in a database and/orfurther analysis. As previously discussed, the monitoring and managementsystems described herein is generally applicable to a variety of energystorage/power systems or energy storage/power system components,including turbine-based power systems, batteries, fuel cell stacks,and/or other types of systems.

For example, the MMS 100 shown in FIG. 1 can be used to monitor and/ormanage the state-of-charge and/or state-of-health of a battery thatpowers an electric vehicle. FIG. 2 illustrates a battery 201 that ismonitored and/or managed by a battery monitoring and management system(BMMS) 200. The monitoring portion of the BMMS comprises a number ofmultiplexed FBG sensors (not shown) embedded within the cells 202 of thebattery 201 and disposed on a single optical fiber (FO) cable 210. TheBMMS system may include one or more FO cables, where each FO cableincludes multiple sensors. In various implementations, the internalparameters of the battery as a whole, e.g., average parameters acrossmultiple cells, and/or internal parameters of one or more of the batterycells can be monitored. A non-limiting illustrative set of parametersthat may be monitored by the sensors includes one or more oftemperature, stress, strain, internal pressure, ion concentration,and/or chemical composition or concentration.

The BMMS 200 includes a light source/analyzer 220 coupled to the FOcable 210. Although one light source/analyzer 220 is shown in FIG. 2, insome configurations multiple light source/analyzers may be respectivelycoupled to multiple FO cables that include multiplexed optical sensors.

Light from the light source 220 is transmitted through the FO cable 210where the transmitted light interacts with the FBG sensors that arespaced apart along the FO cable 210. Reflected light is detected andanalyzed by the analyzer portion of the light source/analyzer 220. Insome implementations, the voltage and/or current of the battery 201and/or other external battery parameters may be measured and provided tothe battery management processor 230.

The FBG sensors are formed by a periodic modulation of the refractiveindex along a finite length (typically a few mm) of the core of the FOcable. This pattern reflects a wavelength, called the Bragg wavelengththat is determined by the periodicity of the refractive index profile ofthe FBG sensor. In practice, the sensor typically reflects a narrow bandof wavelengths centered at the Bragg wavelength. The Bragg wavelength ata characteristic or base value of the external stimulus is denoted λ andlight having wavelength X (and a narrow band of wavelengths near λ) arereflected when the sensor in in the base condition. For example, thebase condition may correspond to 25 degrees C. and/or zero strain. Whenthe sensor is subjected to an external stimulus, such as temperature,strain, or other such stimulus, the stimulus changes the periodicity ofthe grating and the index of refraction of the FBG, and thereby altersthe reflected wavelength to a wavelength, λ_(s), different from the basewavelength, X. The resulting wavelength shift, Δλ/λ=(λ−λ_(s))/λ is adirect measure of the stimulus.

The relation between wavelength shift (Δλ/λ) and simultaneous strain andtemperature in an FBG sensor is:Δλ/λ={1−n ²/2 [p ₁₂ −n(p ₁₁ +p ₁₂)]}∈₁+[α+1/n (dn/dT)]ΔT   [1]

where n is the index of refraction, p₁₁ and p₁₂ are strain-opticconstants, ∈₁ is longitudinal strain, α is the coefficient of thermalexpansion and T is the temperature. In some implementations, by usingmultiple FBG sensors that are differently affected by strain andtemperature (due to design or mounting), dual fibers or special FBGsensors in combination with data evaluation algorithms, the impacts fromstrain and temperature on the wavelength shift can be separated.

Examining the response of FBG sensors quantified in Equation [1], it isclear that these sensors are sensitive to changes in refractive index n,strain ∈₁, and ambient temperature changes ΔT. The refractive index ncan be made sensitive to the chemical environment of the sensor bystripping the FO cladding over the sensor element region and/or byadding appropriate coatings to this sensitive area. Alternately, FBGsensors can be made sensitive to the chemical environment by applyingspecial coatings that convert the chemical composition of theenvironment into a strain signal (e.g. hydrogen sensors based onpalladium coatings). According to embodiments discussed herein, opticalsensors such as FBG sensors are used to detect chemical compositionchanges in battery cells that might affect performance. An example ofthis is formation of a corrosive agent, hydrogen fluoride (HF), inLi-ion cells caused by moisture penetration.

The sensitivity of FBGs to temperature changes allows local temperatureswithin battery cells to be monitored. While this is useful in generalfor battery system management, it is particularly beneficial for earlydetection of thermal runaways. Thermal runaways affect many batterychemistries and can be devastating in Li-ion cells due to their highenergy density. During a thermal runaway, the high heat of the failingcell can propagate to the next cell, causing it to become thermallyunstable as well. In some cases, a chain reaction occurs in which eachcell disintegrates at its own timetable. A pack of battery cells can bedestroyed within a few seconds or can linger on for several hours aseach cell is consumed one-by-one.

The sensitivity of the FBG sensors to strain allows embedding FBGsensors into battery electrodes to monitor the expansion/contractioncycles of the electrodes (which is useful for estimating charge levels,e.g. in Lithium-ion cells). Additionally, electrode strain measurementsallow for examining the degradation of the electrodes, and thus theoverall degradation of the battery. FBG sensitivity to strain alsoallows measurement of internal cell pressure by capturing cell wallstrains.

In measuring power supply parameters using FBG sensors, it can bebeneficial to distinguish between and quantify the individualcontributions of the multiple parameters of interest. In some cases, amulti-sensor configuration may be used so that the parameter of interestcan be compensated for the contributions of other parameters. Forexample, a two-sensor approach may be used for temperature-compensatedchemical sensing, where the two sensors can be arranged in closeproximity. In some implementations, a first sensor of the two sensors isexposed to temperature and is also exposed to the chemical environmentby stripping its cladding. A second sensor of the two sensors used forcompensation retains its cladding and is only sensitive to temperature.Similar configurations may be used for temperature-compensated strainmeasurements and strain-compensated temperature measurements.

For temperature-compensated strain measurements, two FBG sensors areplaced in close proximity where the first sensor is exposed to strainand temperature and a second sensor used for compensation is exposed totemperature but not strain. The temperature measurement of the secondsensor is used to compensate for changes in temperature in the strainmeasurement of the first sensor. For example, the first sensor may beplaced within an electrode or cell wall of a battery and the secondsensor may be placed nearby and/or at a location having about equaltemperature as the location of the first sensor while being subjected toa known and/or non-varying strain. For example, the second sensor may belocated near but not within the electrode or cell wall.

Fiber optic sensors have been demonstrated to withstand and perform invarious harsh environments. The most common material used is silica,which is corrosion resistant, can withstand high tensile strain, and cansurvive between −200° C. and 800° C. Silica-based FBG sensors providerepeatable dependency of their peak wavelength with temperatureconsistently with no thermal hysteresis in tests done up to 300° C. Itis expected that FBG sensors will survive long-term (13-25 years) inlead acid batteries and at least up to a year in HF (a side product ofLi-ion batteries: one year is expected to be longer than the life of theLi-ion battery after HF formation begins). Various types of plastics arealso useful for FO cables and optical sensors. Fiber optic sensors suchas FBG sensors and etalon (FP) sensors are robust with respect to shockand vibration. Thus, embedded fiber optic sensors in energystorage/power systems such as batteries offer an attractive solution toreliably measure and monitor relevant parameters across variousarchitectures and chemistries.

FBG-based sensing allows for incorporating multiple sensing elements,e.g., about 64 sensors, on a single FO cable. Each of the sensors can beindividually interrogated through multiplexing, e.g., WDM or TDM. Onespecial implementation of wavelength division multiplexing for multiplesensors is illustrated in FIG. 3. A broadband light source 310 is usedalong with multiple FBG sensors 321-323. Each of the FBG sensors 321-323are tuned to be primarily reflective to light at different wavelengthbands and are deployed on the same optical fiber spaced apart from eachother along the FO cable and at different distances from the lightsource 310. Each FBG sensor is designated to measure a differentparameter or combination of parameters. The wavelength shifts caused bychanges in the sensed parameters are small compared to the spacingbetween the characteristic base wavelengths of the individual FBGs.Therefore, it is feasible to separate the information from the differentFBGs using linear variable filters or dispersive elements in an opticalWDM scheme. Alternately, an optical TDM scheme can be implemented thatoperates by transmitting a train of short pulses of light in the FOcable, where the wavelengths of the light pulses differ from one anotherand selectively address the various FBG sensors along the FO cable.

FIG. 3 illustrates a monitoring system that monitors multiple parametersof an energy storage/power system with sensor outputs multiplexed usingoptical WDM. As indicted in FIG. 3, broadband light is transmitted bythe light source 310, which may comprise or be a light emitting diode(LED) or superluminescent laser diode (SLD), for example. The spectralcharacteristic (intensity vs. wavelength) of the broadband light isshown by inset graph 391. The light is transmitted via the FO cable 311to the first FBG sensor 321. The first FBG sensor 321 reflects a portionof the light in a first wavelength band having a central or peakwavelength, λ₁. Light having wavelengths other than the first wavelengthband is transmitted through the first FBG sensor 321 to the second FBGsensor 322. The spectral characteristic of the light transmitted to thesecond FBG sensor 322 is shown in inset graph 392 and exhibits a notchat the first wavelength band centered at λ₁ indicating that light inthis wavelength band is reflected by the first sensor 321.

The second FBG sensor 322 reflects a portion of the light in a secondwavelength band having a central or peak wavelength, λ₂. Light that isnot reflected by the second FBG sensor 322 is transmitted through thesecond FBG sensor 322 to the third FBG sensor 323. The spectralcharacteristic of the light transmitted to the third FBG sensor 323 isshown in inset graph 393 and includes notches centered at λ₁ and λ₂.

The third FBG sensor 323 reflects a portion of the light in a thirdwavelength band having a central or peak wavelength, λ₃. Light that isnot reflected by the third FBG sensor 323 is transmitted through thethird FBG sensor 323. The spectral characteristic of the lighttransmitted through the third FBG sensor 323 is shown in inset graph 394and includes notches centered at λ₁, λ₂, and λ₃.

Light in wavelength bands 381, 382, 383, having central wavelengths λ₁,λ₂ and λ₃ (illustrated in inset graph 395) is reflected by the first,second, or third FBG sensors 321, 322, 323, respectively, along the FOcables 311 and 311′ to the analyzer 330. The analyzer 330 may comparethe shifts in each the central wavelengths λ₁, λ₂ and λ₃ and/orwavelength bands reflected by the sensors 321-323 to a characteristicbase wavelength (a known wavelength) to determine whether changes in theparameters sensed by the sensors 321-323 have occurred. The analyzer maydetermine that the one or more of the sensed parameters have changedbased on the wavelength analysis and may calculate a relative orabsolute measurement of the change.

In some cases, instead of emitting broadband light, the light source mayscan through a wavelength range, emitting light in narrow wavelengthbands to which the various sensors disposed on the FO cable aresensitive. The reflected light is sensed during a number of sensingperiods that are timed relative to the emission of the narrowband light.For example, consider the scenario where sensors 1, 2, and 3 aredisposed on a FO cable. Sensor 1 is sensitive to a wavelength band(WB1), sensor 2 is sensitive to wavelength band WB2, and sensor 3 issensitive to WB3. The light source may be controlled to emit lighthaving WB1 during time period 1 and sense reflected light during timeperiod 1 a that overlaps time period 1. Following time period 1 a, thelight source may emit light having WB2 during time period 2 and sensereflected light during time period 2 a that overlaps time period 2.Following time period 2 a, the light source may emit light having WB3during time period 3 and sense reflected light during time period 3 athat overlaps time period 3. Using this version of TDM, each of thesensors may be interrogated during discrete time periods.

The FO cable used for energy storage/power system monitoring maycomprise a single mode (SM) FO cable (as depicted in FIG. 3) or maycomprise a multi-mode (MM) FO cable. While single mode fiber opticcables offer signals that are easier to interpret, to achieve broaderapplicability and lower costs of fabrication, multi-mode fibers may beused.

MM fibers may be made of plastic rather than silica, which is typicallyused for SM fibers. Plastic fibers may have smaller turn radii whencompared with the turn radii of silica fibers, thereby making plasticfibers more practical to embed into battery cells and in individualcells of fuel cell stacks, for example. Furthermore, MM fibers can workwith less expensive light sources (e.g., LEDs) as opposed to SM fibersthat may need more precise alignment with superluminescent diodes(SLDs). Therefore, sensing systems based on optical sensors in MM fibersare expected to yield lower cost systems.

FIG. 4 is an idealized representation of light reflected from a FBGsensor deployed on a SM FO cable. In the characteristic base or knownstate, the FBG sensor reflects light in a relatively narrow wavelengthband 410 having a central or peak wavelength, λ. After the FBG sensorexperiences a change in the sensed condition, e.g., a change intemperature, strain, chemical environment, the light reflected by thesensor shifts to a different wavelength band 420 having a centralwavelength λ_(s). Wavelength band 420 is similar in width, amplitude andother morphological characteristics when compared to wavelength band410, but the central wavelength, λ_(s), of wavelength band 420 isshifted 430 from the central wavelength, λ, of wavelength band 410 by anamount that is related to the change in the sensed condition. Wavelengthbands of similar widths can be identified as wavelength bands havingsimilar full width half maximum (FWHM) values, for example.

FIG. 5 depicts actual data from an FBG sensor deployed on a MM FO cable.FBG sensors deployed on MM FO cables reflect light in multiplewavelength bands in contrast to FBG sensors on SM FO cable where onlyone wavelength band is reflected by the grating. In the characteristicbase condition, the sensor reflects a characteristic spectrum that mayinclude multiple narrower wavelength bands (also referred to as modes)as shown in graph 510. When a change in the sensed parameter occurs, thereflected wavelength spectrum 520 substantially maintains its shape, butis shifted in wavelength in response to the sensed condition. Analyzersdiscussed herein are particularly suited to interrogate MM FBG sensorsbecause these analyzers detect the spectrum centroid (central value ofthe wavelength spectrum modulated envelope) rather than the shift of theindividual modes. FIG. 6 shows the base wavelength spectrum modulatedenvelope 610 of the base wavelength spectrum 510 representing thereflected light when the FBG sensor is in the base condition. Theenvelope 610 may be characterized by a central or peak wavelength,λ_(c), and a FWHM value. When exposed to the sensed condition, thereflected wavelength spectrum modulated envelope 620 of wavelengthspectrum 520 shifts to a new central or peak wavelength, λ_(cs). Theenvelope 620 may be characterized by a FWHM value and the central orpeak wavelength, λ_(cs). The FWHM value of the shifted 620 envelope mayremain substantially unchanged from the base FWHM value, however thecentral or peak wavelength, λ_(cs), is shifted from the base centralwavelength, λ_(c), by an amount related to the change in the sensedparameter.

FIG. 7 shows a portion of Li-ion battery 701 having a SM FO cable 710with multiple optical sensors 721-725 deployed along the SM FO cable 710so that the sensors 721-725 are arranged within the battery 701 atstrategic locations. One or more sensors sense a battery parameter thatis different from battery parameters sensed by one or more other FBGsensors. The battery 701 includes multiple cells, each cell having ananode electrode 702 and a cathode electrode 703 separated by a spacerlayer 704.

The optical sensors include a first strain sensor 721 disposed on orembedded within a first electrode of the battery and a second strainsensor 725 disposed on or embedded within a second electrode of thebattery. In this example, the first and second strain sensors 721, 725are arranged on or within electrodes disposed at opposite sides thebattery 701. The SM FO cable 710 also includes two temperature sensors722, 724. In the embodiment of FIG. 7, a chemical sensor 723 is arrangedbetween the temperature sensors 722, 724.

FIG. 8 depicts a zoomed-in cross section of a portion of the battery 701at the location of sensor 721. The cathode 703 comprises cathodematerial 703 a disposed within an electrolyte matrix 705 and a cathodecollector 703 b. The anode comprises an anode material 702 a disposedwithin the electrolyte matrix 705 and an anode collector 702 b. Theanode 702 and cathode 703 are separated by a separator layer 704. Theportion of the SM FO cable 710 that includes sensor 721 is embeddedwithin the anode 702, where optical sensor 721 may be used to measurestrain and/or temperature of the anode 702.

FIGS. 7 and 8 show one representative embodiment that includes acommercial single-mode fiber optic (SM FO) cable with multiple FBGsensors operating in the 1.55 um wavelength range for temperature,strain, and chemical sensing inserted into a Li-ion battery. To allowdistinguishing between strain and temperature, either special strainsensors or a combination of sensors is used. For example, special strainsensors can be used in conjunction with compensation processesimplemented by the analyzer or the MMS. These compensation processescompensate strain according to temperature. In many cases, thermalresponse time is much slower than elastic response time. Temperaturecompensation/separation can be accomplished where the strain signalchanges at a much higher frequency than temperature (e.g., in a turbinerotating at 50 Hz or a battery discharging quickly in an EV).

Alternatively, two sensors may be used as discussed above where acompensating optical sensor is arranged at a location that is detachedfrom the electrode and thus is sensitive to temperature but is notsubjected to the electrode strain. The signal from the compensatingsensor is used to temperature-compensate the signal from the sensor thatis used to measure electrode strain.

The two temperature sensors 722, 724 can operate at the same wavelengthor both sensors 722, 724 may operate at wavelengths within aninterrogation wavelength band. In either case, the sensors can beinterrogated simultaneously to provide an average cell internaltemperature. Simultaneous interrogation can occur when the light sourceemits interrogation light that includes a wavelength band that bothsensors reflect. The sensor nearest the light source reflects a firstportion of light in the wavelength band and the second sensor reflects asecond portion of the light in the wavelength band. Note that ifmultiple FBG sensors have the same or overlapping wavelength ranges, thereflectivity of the sensors may be relatively low. Otherwise, thereflected signal from the sensor that is farthest from the light sourcewill be reflected by the sensor that is closer to the light source. Thefirst of multiple sensors at a particular wavelength may not besubstantially affected, but every subsequent sensor at that wavelengthmay have reduced sensitivity, depending on the transmitted/reflectedsignal strengths. Two sensors having non-overlapping wavelength rangeswithin the interrogation wavelength range are not so constrained withregard to their reflectivity and can still be interrogatedsimultaneously if the interrogation wavelength range overlaps thewavelength sensitivity ranges of both sensors.

The two strain sensors 721, 725 may also operate in the same wavelengthrange, or within the interrogation wavelength range that is distinctfrom the one used for temperature sensors 722, 724. In the embodimentshown in FIG. 7, the strain sensors 721, 725 are embedded within theoutermost electrodes on opposite sides of the battery 701 to obtainaveraged electrode strain (after compensating for the effect oftemperature) for the battery.

The chemical sensor 723 may be either a functionalized strain sensor,such as a strain sensor having a coating that is reversibly sensitive tothe concentration of a particular chemical/ion solution around it andswells or contracts with increasing/decreasing chemical concentration,thereby reflecting a signal indicative of chemical/ion concentration.Alternatively, a side-polished FBG sensor can be used to sense batterychemistry, where the side polishing exposes the FBG so that changes inthe signal reflected by the sensor are caused by exposure to thechemical environment of the battery. The chemical sensor 723 can be usedto provide information regarding adverse chemical changes in theelectrolyte from aging-related degradation. The five sensors 721-725 maybe illuminated with a broadband light source, e.g., one or multiplesuperluminescence LED or LD, and the reflection peaks produced by thesensors 721-725 will be spectrally separated and uniquely associatedwith each type of FBG sensor 721-725. The spectral shifts in thereflection peaks will be discerned by an analyzer as discussed in moredetail herein. This interrogation technique can be combined with timedivision multiplexing (switching on the different light sources atdifferent times in order to interrogate a certain subgroup of sensors,as described above.

A more economical configuration for commercial applications would use MMFO cables instead of the SM FO cable indicated in FIGS. 7 and 8. MM FOcables have a larger core diameter (typically >50 μm) than SM FOs and,therefore, enable a simplified system assembly. In addition, MM FOs arecapable of using standard LEDs as broadband light sources, which aremuch less expensive than superluminescence LEDs. The analyzers discussedherein are particularly suited for MM FOs with optical sensors disposedthereon because these analyzers are capable of determining the averagewavelength shift of all modes rather than the wavelength shift ofindividual modes. Furthermore, the analyzers discussed herein arelargely insensitive to the FWHM of the incoming light.

Typical wavelength shifts for FBG temperature sensors are about 10 pm/Kso that a representative dynamic range of 100° C. corresponds to a totalwavelength change of 1 nm. With an expected wavelength detectionaccuracy of 10 pm in MM fibers (with 30 fm demonstrated in SM fibers) atemperature accuracy of 1° C. is achievable. With regard to strainmeasurements, for reported volume changes of 10% in Li-cell electrodes,total length changes in each direction of the electrode of approximately3.2% are estimated. Thus, FBG strain sensors are well suited formeasuring relative length changes of 100 μ∈, even with MM fibers. Thisimplies an accuracy of 1/320th or better of the minimum 3.2% peak straintypical in Li-ion electrodes. For sensing adverse chemical compositionchanges (HF formation in the case of Li-ion cells), 50 ppm HFdetectability may be achieved. Detection of HF ingress at this levelwill suffice for early HF detection indicative of problematic seals orother moisture ingress issues that can rapidly age the cell electrodes.

FIG. 9 is a block diagram illustrating portions of a light source andanalyzer 900 that may be used to detect and/or interpret optical signalsreceived from an MM or SM FO cable having multiple optical sensorsarranged at locations in, on or about an energy storage/power system.The light source 905 transmits input light to the sensors via FO 906.The analyzer 900 includes various components that may optionally be usedto analyze the light reflected by the sensors and propagated by FO 910.The analyzer 900 includes an optional spreading component 940 configuredto collimate and/or spread the light from the FO cable 910 across aninput surface of a linearly varying transmission structure (LVTS) 930.In arrangements where sufficient spreading of the light occurs from theFO, the spreading component may not be used. The LVTS 930 may comprise adispersive element, such as a prism, or linear variable filter. The LVTS930 receives light at its input surface 931 (from the FO 910 and(optionally) the spreading component 940) and transmits light from itsoutput surface 932. At the output surface 932 of the LVTS 930, thewavelength of the light varies with distance along the output surface932. Thus, the LVTS 930 can serve to demultiplex the optical signalincident at the input surface 931 of the LVTS 930 according to thewavelength of the light. FIG. 9 shows two wavelength bands (calledemission band) emitted from the LVTS 930, a first emission band has acentral wavelength of λ_(a) emitted at distance d_(a) from a referenceposition (REF) along the output surface 932. The second emission bandhas a central wavelength λ_(b) and is emitted at distance d_(b) from thereference position. A position sensitive detector (PSD) 950 ispositioned relative to the LVTS 930 so that light transmitted throughthe LVTS 930 falls on the PSD. For example, light having wavelengthλ_(a) falls on region a of the PSD 950 and light having wavelength λ_(b)falls on region b of the PSD 950. The PSD generates an electrical signalalong output 951 that includes information about the position (and thusthe wavelength) of the light output from the LVTS. The output signalfrom the PSD is used by the processor 960 to detect shifts in thewavelengths reflected by the sensors.

The PSD may be or comprise a non-pixelated detector, such as a largearea photodiode, or a pixelated detector, such as a photodiode array orcharge coupled detector (CCD). Pixelated one-dimensional detectorsinclude a line of photosensitive elements whereas a two-dimensionalpixelated detector includes an n x k array of photosensitive elements.Where a pixelated detector is used, each photosensitive element,corresponding to a pixel, can generate an electrical output signal thatindicates an amount of light incident on the element. The processor 960may be configured to scan through the output signals to determine thelocation and location changes of the transmitted light spot. Knowing theproperties of the LVTS allows determining peak wavelength(s) and shiftof the peak wavelength(s) of the first and/or second emission band. Thewavelength shift of the first or second emission band can be detected asa shift of the transmitted light spot at location a or b. This can, forexample, be accomplished by determining the normalized differentialcurrent signal of certain pixels or pixel groups of the PSD.

For example, consider the example where light spot A having emissionband EB_(A) is incident on the PSD at location a. I_(a1) is the currentgenerated in the PSD by light spot A by pixel/pixel group at location aland I_(a2) is the current generated in the PSD by light spot A bypixel/pixel group at location a2. Light spot B having emission bandEB_(B) is incident on the PSD at location b. I_(b1) is the currentgenerated in the PSD by light spot B by pixel/pixel group at location b1and I_(b2) is the current generated in the PSD by light spot B bypixel/pixel group at location b2.

The normalized differential current signal generated by pixels or pixelgroups at locations a1 and a2 can be written(I_(a1)−I_(a2))/(I_(a1)+I_(a2)), which indicates the position of lightspot A on the PSD. The wavelength of EB_(A) can be determined from theposition of light spot A on the PSD.

Similarly, the normalized differential current signal generated bypixels or pixel groups at locations b1 and b2 can be written(I_(b1)−I_(b2))/(I_(b1)+I_(b2)), which indicates the position of lightspot B on the PSD. The wavelength of EB_(B) can be determined from theposition of light spot B on the PSD.

FIG. 10 is a block diagram illustrating portions of an analyzer 1000that includes a non-pixelated, one-dimensional PSD 1050. The analyzer1000 includes an optional spreading component 1040 that is similar tospreading component 940 as previously discussed. The spreading component1040 is configured to collimate and/or spread the light from the FOcable 1010 across an input surface 1031 of a linearly varyingtransmission structure (LVTS) 1030. In the implementation depicted inFIG. 10, the LVTS 1030 comprises a linear variable filter (LVF) thatcomprising layers deposited on the PSD 1050 to form an integratedstructure. The LVF 1030 in the illustrated example comprises twomirrors, e.g., distributed Bragg reflectors (DBRs) 1033, 1034 that arespaced apart from one another to form optical cavity 1035. The DBRs1033, 1034 may be formed, for example, using alternating layers of highrefractive index contrast dielectric materials, such as SiO₂ and TiO₂.One of the DBRs 1033 is tilted with respect to the other DBR 1034forming an inhomogeneous optical cavity 1035. It will be appreciatedthat the LVF may alternatively use a homogeneous optical cavity when thelight is incident on the input surface at an angle.

The PSD 1050 shown in FIG. 10 is representative of a non-pixelated,one-dimensional PSD although two-dimensional, non-pixelated PSDs (andone or two-dimensional pixelated PSDs) are also possible. The PSD 1050may comprise, for example, a large area photodiode comprising asemiconductor such as InGaAs. Two contacts 1053, 1054 are arranged torun along first and second edges of the semiconductor of the PSD tocollect current generated by light incident on the surface of the PSD1050. When a light spot 1099 is incident on the PSD 1050, the contactnearest the light spot collects more current and the contact fartherfrom the light spot collects a lesser amount of current. The currentfrom the first contact 1053 is denoted I₁ and the current from thesecond contact 1054 is denoted I₂. The processor 1060 is configured todetermine the normalized differential current, (I₁+I₂)/(I₁+I₂), theposition of the transmitted light spot, and therefore the predominantwavelength of the light incident at the input surface 1031 of the LVTS1030 can be determined. The predominant wavelength may be compared toknown wavelengths to determine an amount of shift in the wavelength. Theshift in the wavelength can be correlated to a change in the sensedparameter. In case two emission bands (creating two spatially separatedlight spots) hitting the detector at the same time the detector is onlycapable to provide an average wavelength and wavelength shifts for bothemission bands. If wavelength and wavelengths shift of both emissionbands need to be determined separately the two emission bands need tohit the detector at different time (time multiplexing).

In other embodiments, a two dimensional non-pixelated PSDs may be used,with edge contacts running along all four edges. The position of thecentral reflected wavelength may be determined by analyzing the currentcollected from each of the four contacts. The portion of the analyzershown in FIG. 10 may be packaged together in a suitable housing, e.g.,TO5 transistor header, as shown in FIG. 11.

Sensed parameter information can be combined with modeling of the powersystem, e.g., battery, to estimate operating variables of the batterysuch as state-of-charge and/or state-of-health. FIG. 12 is a flowdiagram that illustrates processes to determine SOC and SOH. EstimatingSOH and/or SOC may be performed in a variety of ways. One embodimentcould be to develop models for the battery operation and the measurementscheme, either through physical modeling from first principles or fromdata-driven machine learning from characterization experiments. Thebattery operational model 1210 encapsulates how the battery statevariables like charge, ion-concentration, voltage, temperature, or asubset thereof changes based on load and environmental factors likecurrent, ambient temperature and pressure, or some subset of these. Thebattery measurement model 1212 expresses the relation between the sensedparameters 1205 from the FO sensors in the battery cells and the batterystate variables, and includes the behavioral dynamics of the sensor.Information from these two models as well as the sensed values can becombined by state tracking, filtering or estimation techniques toestimate the remaining charge in the battery 1215. Crude estimates ofSOC may be derived by dividing this charge by the expected totalcapacity of the battery. However, the not all the remaining charge maybe usable since it depends on the load and environmental factors as wellas the cutoff thresholds of the associated BMMS. Hence, a stochasticdistribution of the intended future usage can be used to derive theremaining useful charge 1225 and then this value can be used to estimate1230 the SOC or the “usable” SOC.

A similar process can be followed for the SOH calculations, where thebattery capacity estimation model 1235 that computes the present batterycapacity as the sum of the measured charge used (Coulomb counting) andthe remaining usable charge, and the battery capacity loss model 1240that indicates how the capacity changes from one cycle (a fulldischarge-charge event is called a cycle) to another based oncycle-life, usage conditions and storage environment, can be combined tobetter estimate 1245 the present battery capacity. Note that each modelindividually can be used to the get the capacity from the current cyclemeasurements or the previous cycle measurements, respectively. However,due to sensor errors, model uncertainties and the fact that most realusage cycles are partial cycles, the combined capacity estimate isbetter than the individual ones. Subsequently, a stochastic distribution1250 of the future cycle life can be used to predict 1255 the number ofcycles left until the capacity falls below an end-of-life threshold. TheSOH can then be computed 1260 as the fraction of present capacity overrated capacity or the remaining cycles over the expected total number ofcycles. The SOH can also be derived from internal parameters like thebattery impedance and mapping it to capacity or cycle life using machinelearning techniques applied over experimental or operational data.

Other embodiments may skip parts of the modeling steps and may derivedirect relations between the sensed values and the battery states (SOCand SOH) by using techniques like neural networks or other machinelearning algorithms.

Embodiments disclosed herein involve multiplexed optical sensors on asingle optical fiber embedded within various components of an energystorage/power system such as within individual cells of a battery. Whenused in battery applications, the monitoring and management systemsdescribed herein are capable of measuring electrode strain, ionconcentrations, internal temperature, internal pressure, and/or adversechemical compositions, each of which are internal cell-state variablesof the battery. According to one embodiment, 25 sensors are multiplexedwith acquisition frequency of about 100 Hz. The strain measurementaccuracy is about 10 μ∈ for the multiplexed SM FO version or 100 μ∈ forthe multiplexed MM FO version. Strain measurement accuracy of 100 μ∈ issufficient to measure electrode strains for Li-ion cells (which havepeak strain amplitudes of 32000 μ∈ or higher) and cell pressure withsufficient accuracy for SOC/SOH determination. A temperature measurementaccuracy of about 0.5° C. for the multiplexed SM FO version and 1° C.for the multiplexed MM FO version can be achieved. Temperaturemeasurement accuracy of 1° C. is sufficient for early detection ofthermal runaways and also to account for model compensation to determineSOC. In some embodiments, the monitoring and management system iscapable of detecting adverse chemical composition. For example, both themultiplexed SM FO version and multiplexed MM FO version of the systemare capable of detecting 50 ppm HF concentration.

As previously discussed, since such optical sensors can survive harshenvironments and loads over expected lifetimes of such systems and areinherently immune to EMI, they are not expected to suffer from reducedsensitivity in field applications due to interference from the manyother high-duty electronic components in practical applications such aselectric vehicles (EVs).

Due to the small form factor and light weight of optical fibers (100-500μm dia. and density of 1-1.5 g/cc) and the compactness of the analyzer,volume and weight overheads of the monitoring and management system areexpected to be minimal (<0.05% volume overhead within the cell, <0.1%volume overhead overall; and <0.05% weight within the cell, <0.1% weightoverall).

Due to the minimal volume overhead of thin fiber optic cables, theenergy density will also have minimal impact (<0.05% energy densityoverhead), which is well compensated by the benefits of accurateinternal cell-state measurement, which include reductions inconservative oversizing. Since the signals are entirely optical, therewill be no interference with the internal voltage field of the cell(unlike reference electrodes). As summarized earlier, the FO material isbenign and robust to various harsh environments, including Pb-acidbatteries and HF. By careful choice of the FO ingress point (e.g., at anelectrode), the thin FO cable is not expected to affect cell sealing.

The specifications for the monitoring and management systems detailedabove allow real-time (at 100 Hz) detection of a broad variety of cellfaults ranging from design flaws, manufacturing defects, and aggressiveoperation, each of which would result in abrupt changes or anomalies ininternal cell parameters of magnitude well over these resolution limittargets. Thus, it is feasible to approach 100% diagnostic sensitivity.The immunity to EMI and ability to function in harsh environmentswithout degraded performance implies that false alarms from such systemswill be minimal, thereby making it realistic to achieve >95% diagnosticspecificity.

The capability to accurately detect cell faults with high sensitivityand specificity implies that the control strategy can reliably uncoupleor reduce the demands on weaker/defective cells early, thereby allowingthe pack to function safely through adaptive management and preventingcatastrophic failure events such as thermal runaways.

Due to uncertainties in estimates of internal cell-state variables, mostcommercial Li-ion battery systems today are conservatively designed andthus only allow access to 10-80% of their stored energy capacity.Embodiments disclosed herein enable internal cell state measurement interms across a number of variables and prognostic algorithms that enablehigh-accuracy (2.5%) predictions of remaining life, allowing reductionsin conservative over-design. In addition, using algorithms that arebased on accurate internal cell state measurements, it is feasible toget more accurate state-of-health estimates and extend cell life,resulting in even greater reductions in over-sizing design practices.

Accurate internal cell-state measurements can allow informed decisionsabout whether faster charging cycles are adversely impacting aparticular cell in a pack. This can allow for optimized charging cycles,which account for cell-to-cell manufacturing/state of health variation.

Systems, devices, or methods disclosed herein may include one or more ofthe features, structures, methods, or combinations thereof describedherein. For example, a device or method may be implemented to includeone or more of the features and/or processes described herein. It isintended that such device or method need not include all of the featuresand/or processes described herein, but may be implemented to includeselected features and/or processes that provide useful structures and/orfunctionality.

In the above detailed description, numeric values and ranges areprovided for various aspects of the implementations described. Thesevalues and ranges are to be treated as examples only, and are notintended to limit the scope of the claims. For example, embodimentsdescribed in this disclosure can be practiced throughout the disclosednumerical ranges. In addition, a number of materials are identified assuitable for various implementations. These materials are to be treatedas exemplary, and are not intended to limit the scope of the claims.

The foregoing description of various embodiments has been presented forthe purposes of illustration and description and not limitation. Theembodiments disclosed are not intended to be exhaustive or to limit thepossible implementations to the embodiments disclosed. Manymodifications and variations are possible in light of the aboveteaching.

The invention claimed is:
 1. A system, comprising: one or moremulti-mode fiber optic cables arranged within or on portions of anenergy storage device, each fiber optic cable including multiple opticalsensors, at least one of the optical sensors configured to sense aparameter of the energy storage device that is different from aparameter of the energy storage device sensed by at least anotheroptical sensor of the multiple optical sensors; a light sourceconfigured to provide light to the one or more fiber optic cables; adetector configured to detect light reflected by the optical sensors andto generate an electrical signal based on the reflected light; and aprocessor coupled to receive the electrical signal, to analyze theelectrical signal and to determine state of the energy storage devicebased on analysis of the electrical signal.
 2. The system of claim 1,wherein each of the multiple optical sensors comprises one or more of asensor configured to sense mechanical strain of a component of theenergy storage device, a sensor configured to sense cell wall pressureof the energy storage device, and a sensor configured to sense chemistryinside the energy storage device.
 3. The system of claim 1, wherein themultiple optical sensors comprise at least one sensor configured tosense temperature, at least one sensor configured to sense mechanicalstrain of an energy storage device component, and at least one sensorconfigured to sense chemistry inside the energy storage device.
 4. Thesystem of claim 1, wherein at least one of the multiple sensors is areference sensor used to compensate a parameter of the energy storagedevice sensed by another sensor.
 5. The system of claim 1 wherein one ofthe multiple sensors comprises a strain sensor configured to measurestrain of a component of the energy storage device and another sensor ofthe multiple sensors comprises a temperature sensor configured tomeasure temperature of the component, wherein an output of thetemperature sensor is used to temperature-compensate an output of thestrain sensor.
 6. The system of claim 1, wherein one or more of theoptical sensors comprise fiber Bragg grating sensors.
 7. The system ofclaim 1, wherein one or more of the optical sensors comprise Fabry-Perotsensors.
 8. The system of claim 1, further comprising an optical elementcoupled between the fiber optic cable and the detector, the opticalelement configured to demultiplex optical signals from the multiplesensors.
 9. The system of claim 8, wherein the optical element comprisesa linear variable filter.
 10. The system of claim 1, wherein: the lightsource is configured to emit pulses of light separated in time,including a least a first narrow wavelength band light pulse having afirst peak wavelength emitted at a first time and a second narrowwavelength band light pulse having a second peak wavelength emitted at asecond time; a first sensor of the multiple sensors is substantiallyresponsive to the first peak wavelength and is substantiallyunresponsive to the second peak wavelength; and the second sensor issubstantially responsive to the second peak wavelength and issubstantially unresponsive to the first peak wavelength.
 11. The systemof claim 1, wherein the multiple sensors include two first sensorsconfigured to sense a first energy storage device parameter and a secondsensor configured to sense a second energy storage device parameterwherein and the two first sensors are substantially responsive to afirst peak wavelength and are substantially unresponsive to a secondpeak wavelength and the second sensor is substantially responsive to thesecond peak wavelength and is substantially unresponsive to the firstpeak wavelength.
 12. The system of claim 1, wherein the light source isa broad wavelength band light source.
 13. The system of claim 1, whereinthe energy storage device comprises a battery disposed within anelectric vehicle.
 14. A system, comprising: one or more fiber opticcables arranged within or on portions of an energy storage device, eachfiber optic cable including multiple optical sensors, at least one ofthe optical sensors configured to sense a parameter of the energystorage device that is different from a parameter of the energy storagedevice sensed by at least another optical sensor of the multiple opticalsensors; a light source configured to provide light to the one or morefiber optic cables; a detector configured to detect light reflected bythe optical sensors and to generate an electrical signal based on thereflected light; and a processor coupled to receive the electricalsignal, to analyze the electrical signal and to determine state of theenergy storage device based on analysis of the electrical signal.
 15. Amethod, comprising: transmitting light into one or more fiber opticcables, the fiber optic cables arranged within or on components of anenergy storage device, each fiber optic cable including multiple opticalsensors, at least one of the optical sensors configured to sense aninternal parameter of the energy storage device that is different from aparameter sensed by at least one other optical sensor of the multipleoptical sensors; detecting light reflected by one or more of themultiple optical sensors and generating an electrical signal in responseto detecting the reflected light; analyzing the electrical signal; anddetermining state of the energy storage device based on analysis of theelectrical signal.
 16. The method of claim 15, further comprising:demultiplexing the reflected light; and detecting the demultiplexedlight.
 17. The method of claim 15, wherein analyzing the electricalsignal comprises detecting shifts between a spectrum of lighttransmitted into the one or more fiber optic cables and a spectrum ofthe reflected light.
 18. The method of claim 17, wherein: at least oneof the fiber optic cables comprises a multi-mode fiber optic cable; andthe spectrum of the reflected light is a multi-modal spectrum.
 19. Themethod of claim 15, wherein: transmitting the light comprisingtransmitting light having a first peak wavelength; and determining thestate of the battery comprises determining an average value for thefirst battery parameter based on a portion of the light having the firstpeak wavelength that is reflected by two or more of the sensors.
 20. Themethod of claim 15, further comprising sensing external parameters ofthe energy storage device including one or more of battery voltage andcurrent.